Unmanned Air Vehicles (UAVs) lend themselves to provide rescue forces with important information beyond their own field of vision. In this paper, we present a two-part yet synergetic navigation and mapping system for indoor reconnaissance and surveillance through aerial platforms. It faces inherent drawback of common Simultaneous Localization and Mapping (SLAM) approaches: map errors cannot be excluded and will directly afflict the positioning. With a flexible navigation filter and an efficient 2.5D mapping tool as centerpieces, our system facilitates appropriate mutual feedback of supporting information. That is map-based navigation aiding in terms of ego-motion estimation and improved mapping in terms of accuracy, robustness and efficiency. Hereby both modules remain independent in their basic function and are therefore guarded against overlapping errors. Finally, the system is validated by means of real experimental data and a first proof of suitability for application within autonomous exploration is given based on simulated flights.